CV

Education

• Ph.D in Astrophysics, Vanderbilt University, 2023
  • Thesis: Characterizing Open Clusters and Spectroscopic Eclipsing Binaries with Machine Learning Frameworks
• M.S. in Physics, Fisk University, 2017
• B.S. in Astronomy, University of Florida, 2011

Skills

• Languages
  • Python (Numba, NumPy, Pandas, Sci-kit Learn, SciPy)
  • SQL
• Frameworks
  • HuggingFace, NLTK, OpenCV, PySpark, TensorFlow, Jupyter
• Analytics
  • Descriptive Statistics
  • Predictive Analysis
  • Bayesian Inference
• Machine Learning
  • Data Mining & Data Engineering
  • Model Selection & Model Validation
  • Clustering
  • Random Forests
  • Gaussian Processes
  • MCMC
  • Deep Learning
  • Bayesian Networks
• SQL
• Visualizations
  • Python
    • Matplotlib, Seaborn, Plotly, Bokeh
  • Tableau
• Software Development
  • Docker, Github, Jupyter, Streamlit
• Languages
  • English (primary), Spanish (secondary)
• Soft-Skills
  • Research
  • Presentations (PowerPoint, Keynote)
  • Mentoring

Work experience

• 01.2024 - Present: Part-time AI/ML Instructor, AI-4-ALL
  • Conducted lectures in AI/ML technical concepts to undergraduates
  • Guided class discussions on ethical/responsible usages of AI technologies
  • Advised on curriculum improvements for greater student engagement
• 01.2022 - 08.2023: Researcher, Vanderbilt University
  • Mentored junior researcher on position-velocity clustering with deconvolutional algorithm
  • Constructed pipeline for multi-sourced data mining of astronomical data from online databases
  • Increased detection sensitivity in astronomical survey by 11% with Gaussian Mixture Models
• 08.2021-01.2022: Data Analyst, Center for Computational Astrophysics, Flatiron Institute
  • Achieved less than 3% error with Bayesian inference framework for time-series data
  • Leveraged Gaussian process models for denoising sparse time-series data
  • Optimized python software for teaching astronomy concepts
• 05.2019-08.2021: Graduate Researcher, Vanderbilt University
  • Created automated clustering pipeline for noisy data with greater than 95% accuracy
  • Increased clustering algorithm sensitivity by 11%
  • Implemented written python code to automate hundreds of custom SQL queries
  • Performed outlier detection of clusters with probabilistic graph analysis

Certifications

• Correlation-One
  • Data Skills 4 All
• Alteryx
  • Machine Learning Fundamentals
  • Foundation

Teaching

2017 Outreach for Total Solar Eclipse Readiness

2018-Spring-Astro-Lab

2024-Spring-AI-4-ALL